SINS/GPS Tightly Integrated Navigation Algorithm for Land Vehicle Applications

This paper discusses the design of SINS/GPS adaptive Kalman filtering algorithm based on motion constraints for land vehicle applications. The algorithm adopts the architecture of tight integration which can continue to work even with no more than four GPS satellites. The vehicle motion constraints enhance the observation of the integrated navigation when satellite is outage. Adaptive Kalman filter with forgetting factor improves robustness of the integrated system. Some experiments are carried out and the results show that the proposed algorithm advances the performance of SINS/GPS integrated system. It gains better position accuracy 4.86 times and better velocity accuracy 1.23 times than traditional Kalman filtering algorithm.